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Coded grouping-based inspection algorithms to detect malicious meters in neighborhood area smart grid
Xia XF(夏小芳)1,2,3; Xiao Y(肖杨)4; Liang W(梁炜)1,2; Zheng M(郑萌)1,2
Department工业控制网络与系统研究室
Source PublicationComputers and Security
ISSN0167-4048
2018
Volume77Pages:547-564
Indexed BySCI ; EI
EI Accession number20182305271947
WOS IDWOS:000447358600032
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China (NSFC) ; NSFC ; National Key Research and Development Program of China ; Youth Innovation Promotion Association, Chinese Academy of Sciences
KeywordSmart Grid Malicious Meter Inspection Theft Of Electricity Grouping Intrusion Detection Security
Abstract

When modern hardware and software technologies are integrated into smart grid, numerous vulnerabilities are introduced at the same time. The vulnerabilities are now leveraged by malicious users for the purpose of electricity theft. Many approaches are proposed to identify malicious users. However, some of them have low detection rates; the others suffer from either low inspection speed or huge cost of deploying monitoring devices. In this paper, to accurately locate malicious users stealing electricity in a fast and economic way, we propose three novel inspection algorithms. First, Binary-Coded Grouping-based Inspection (BCGI) algorithm is proposed. Under some assumptions, it can locate malicious users with only one inspection step. Given n users, the BCGI algorithm requires Θ(log2(n)) inspectors. Unfortunately, in some cases we do not have enough inspectors for the BCGI algorithm to work. To deal with these cases, we further propose two algorithms: M-ary Coded Grouping-based Inspection (MCGI) and Generalized BCGI (G-BCGI). In the MCGI algorithm, users’ identification (ID) numbers are encoded into (l+1)-nary notations, where l is adaptively determined by the number of users and the number of available inspectors. It can locate malicious users within l inspection steps. In G-BCGI algorithm, users’ IDs are encoded into binary notations, similar to the BCGI algorithm, and multiple rounds may be needed to locate malicious users. Experiment results show that the proposed algorithms can locate malicious users accurately and efficiently.

Language英语
WOS SubjectComputer Science, Information Systems
WOS KeywordNONTECHNICAL LOSS FRAUD ; ELECTRICITY THEFT ; NETWORKS
WOS Research AreaComputer Science
Funding ProjectNational Natural Science Foundation of China (NSFC)[61374200] ; NSFC[61673371] ; NSFC[71661147005] ; National Key Research and Development Program of China[2017YFE0101300] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[2015157]
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/21900
Collection工业控制网络与系统研究室
Corresponding AuthorXiao Y(肖杨)
Affiliation1.Key Lab of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China;
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
3.University of Chinese Academy of Sciences, Beijing 100049, China;
4.Department of Computer Science, The University of Alabama, Tuscaloosa AL 35487-0290, United States
Recommended Citation
GB/T 7714
Xia XF,Xiao Y,Liang W,et al. Coded grouping-based inspection algorithms to detect malicious meters in neighborhood area smart grid[J]. Computers and Security,2018,77:547-564.
APA Xia XF,Xiao Y,Liang W,&Zheng M.(2018).Coded grouping-based inspection algorithms to detect malicious meters in neighborhood area smart grid.Computers and Security,77,547-564.
MLA Xia XF,et al."Coded grouping-based inspection algorithms to detect malicious meters in neighborhood area smart grid".Computers and Security 77(2018):547-564.
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